2,673 research outputs found

    An examination of the verbal behaviour of intergroup discrimination

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    This thesis examined relationships between psychological flexibility, psychological inflexibility, prejudicial attitudes, and dehumanization across three cross-sectional studies with an additional proposed experimental study. Psychological flexibility refers to mindful attention to the present moment, willing acceptance of private experiences, and engaging in behaviours congruent with one’s freely chosen values. Inflexibility, on the other hand, indicates a tendency to suppress unwanted thoughts and emotions, entanglement with one’s thoughts, and rigid behavioural patterns. Study 1 found limited correlations between inflexibility and sexism, racism, homonegativity, and dehumanization. Study 2 demonstrated more consistent positive associations between inflexibility and prejudice. And Study 3 controlled for right-wing authoritarianism and social dominance orientation, finding inflexibility predicted hostile sexism and racism beyond these factors. While showing some relationships, particularly with sexism and racism, psychological inflexibility did not consistently correlate with varied prejudices across studies. The proposed randomized controlled trial aims to evaluate an Acceptance and Commitment Therapy intervention to reduce sexism through enhanced psychological flexibility. Overall, findings provide mixed support for the utility of flexibility-based skills in addressing complex societal prejudices. Research should continue examining flexibility integrated with socio-cultural approaches to promote equity

    A review of differentiable digital signal processing for music and speech synthesis

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    The term “differentiable digital signal processing” describes a family of techniques in which loss function gradients are backpropagated through digital signal processors, facilitating their integration into neural networks. This article surveys the literature on differentiable audio signal processing, focusing on its use in music and speech synthesis. We catalogue applications to tasks including music performance rendering, sound matching, and voice transformation, discussing the motivations for and implications of the use of this methodology. This is accompanied by an overview of digital signal processing operations that have been implemented differentiably, which is further supported by a web book containing practical advice on differentiable synthesiser programming (https://intro2ddsp.github.io/). Finally, we highlight open challenges, including optimisation pathologies, robustness to real-world conditions, and design trade-offs, and discuss directions for future research

    "It's not a career": Platform work among young people aged 16-19

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    In the online gig economy, or platform work as it is sometimes known, work can be organised through websites and smartphone apps. People can drive for Uber or Deliveroo, sell items on eBay or Etsy, or rent their properties on Airbnb. This research examines the views of young people between the ages of 16 and 19 in the United Kingdom to see whether they knew about the online gig economy, whether they were using it already to earn money, and whether they expected to use it for their careers. It discovers careers professionals’ levels of knowledge, and their ability (and desire) to include the gig economy in their professional practice. This research contributes to discussions about what constitutes decent work, and whether it can be found within the online gig economy. The results point to ways in which careers practice could include platform work as a means of extending young people’s knowledge about alternative forms of work. This study also makes a theoretical contribution to literature, bringing together elements of careership, cognitive schema theory, and motivational theory and psychology of working theory, in a novel combination, to explain how young people were thinking about platform work in the context of their careers

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Increasing trust in new data sources: crowdsourcing image classification for ecology

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    Crowdsourcing methods facilitate the production of scientific information by non-experts. This form of citizen science (CS) is becoming a key source of complementary data in many fields to inform data-driven decisions and study challenging problems. However, concerns about the validity of these data often constrain their utility. In this paper, we focus on the use of citizen science data in addressing complex challenges in environmental conservation. We consider this issue from three perspectives. First, we present a literature scan of papers that have employed Bayesian models with citizen science in ecology. Second, we compare several popular majority vote algorithms and introduce a Bayesian item response model that estimates and accounts for participants' abilities after adjusting for the difficulty of the images they have classified. The model also enables participants to be clustered into groups based on ability. Third, we apply the model in a case study involving the classification of corals from underwater images from the Great Barrier Reef, Australia. We show that the model achieved superior results in general and, for difficult tasks, a weighted consensus method that uses only groups of experts and experienced participants produced better performance measures. Moreover, we found that participants learn as they have more classification opportunities, which substantially increases their abilities over time. Overall, the paper demonstrates the feasibility of CS for answering complex and challenging ecological questions when these data are appropriately analysed. This serves as motivation for future work to increase the efficacy and trustworthiness of this emerging source of data.Comment: 25 pages, 10 figure

    Talking about personal recovery in bipolar disorder: Integrating health research, natural language processing, and corpus linguistics to analyse peer online support forum posts

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    Background: Personal recovery, ‘living a satisfying, hopeful and contributing lifeeven with the limitations caused by the illness’ (Anthony, 1993) is of particular value in bipolar disorder where symptoms often persist despite treatment. So far, personal recovery has only been studied in researcher-constructed environments (interviews, focus groups). Support forum posts can serve as a complementary naturalistic data source. Objective: The overarching aim of this thesis was to study personal recovery experiences that people living with bipolar disorder have shared in online support forums through integrating health research, NLP, and corpus linguistics in a mixed methods approach within a pragmatic research paradigm, while considering ethical issues and involving people with lived experience. Methods: This mixed-methods study analysed: 1) previous qualitative evidence on personal recovery in bipolar disorder from interviews and focus groups 2) who self-reports a bipolar disorder diagnosis on the online discussion platform Reddit 3) the relationship of mood and posting in mental health-specific Reddit forums (subreddits) 4) discussions of personal recovery in bipolar disorder subreddits. Results: A systematic review of qualitative evidence resulted in the first framework for personal recovery in bipolar disorder, POETIC (Purpose & meaning, Optimism & hope, Empowerment, Tensions, Identity, Connectedness). Mainly young or middle-aged US-based adults self-report a bipolar disorder diagnosis on Reddit. Of these, those experiencing more intense emotions appear to be more likely to post in mental health support subreddits. Their personal recovery-related discussions in bipolar disorder subreddits primarily focussed on three domains: Purpose & meaning (particularly reproductive decisions, work), Connectedness (romantic relationships, social support), Empowerment (self-management, personal responsibility). Support forum data highlighted personal recovery issues that exclusively or more frequently came up online compared to previous evidence from interviews and focus groups. Conclusion: This project is the first to analyse non-reactive data on personal recovery in bipolar disorder. Indicating the key areas that people focus on in personal recovery when posting freely and the language they use provides a helpful starting point for formal and informal carers to understand the concerns of people diagnosed with bipolar disorder and to consider how best to offer support

    Microcredentials to support PBL

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    Evacuação de Edifícios – Caso de estudo de um edifício escolar

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    O objetivo deste trabalho é o levantamento dos aspetos que influenciam o tempo de evacuação num edifício escolar, desde o comportamento humano às caraterísticas físicas do edifício e às metodologias possíveis de adotar para a gestão da emergência, com vista a calcular o tempo necessário e disponível para a evacuação do referido edifício. A evacuação de edifícios em situação de incêndio tem como propósito a proteção da vida humana que é inseparável das condições de emergência as quais são afetadas por fatores de difícil determinação e que necessitam de ser definidos para estimar o tempo e as condições de evacuação.info:eu-repo/semantics/publishedVersio

    Reframing museum epistemology for the information age: a discursive design approach to revealing complexity

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    This practice-based research inquiry examines the impact of an epistemic shift, brought about by the dawning of the information age and advances in networked communication technologies, on physical knowledge institutions - focusing on museums. The research charts adapting knowledge schemas used in museum knowledge organisation and discusses the potential for a new knowledge schema, the network, to establish a new epistemology for museums that reflects contemporary hyperlinked and networked knowledge. The research investigates the potential for networked and shared virtual reality spaces to reveal new ‘knowledge monuments’ reflecting the epistemic values of the network society and the space of flows. The central practice for this thesis focuses on two main elements. The first is applying networks and visual complexity to reveal multi-linearity and adapting perspectives in relational knowledge networks. This concept was explored through two discursive design projects, the Museum Collection Engine, which uses data visualisation, cloud data, and image recognition within an immersive projection dome to create a dynamic and searchable museum collection that returns new and interlinking constellations of museum objects and knowledge. The second discursive design project was Shared Pasts: Decoding Complexity, an AR app with a unique ‘anti-personalisation’ recommendation system designed to reveal complex narratives around historic objects and places. The second element is folksonomy and co-design in developing new community-focused archives using the community's language to build the dataset and socially tagged metadata. This was tested by developing two discursive prototypes, Women Reclaiming AI and Sanctuary Stories
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